{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Chapter 7 – Ensemble Learning and Random Forests**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "_This notebook contains all the sample code and solutions to the exercices in chapter 7._"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "First, let's make sure this notebook works well in both python 2 and 3, import a few common modules, ensure MatplotLib plots figures inline and prepare a function to save the figures:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# To support both python 2 and python 3\n",
    "from __future__ import division, print_function, unicode_literals\n",
    "\n",
    "# Common imports\n",
    "import numpy as np\n",
    "import numpy.random as rnd\n",
    "import os\n",
    "\n",
    "# to make this notebook's output stable across runs\n",
    "rnd.seed(42)\n",
    "\n",
    "# To plot pretty figures\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['axes.labelsize'] = 14\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "\n",
    "# Where to save the figures\n",
    "PROJECT_ROOT_DIR = \".\"\n",
    "CHAPTER_ID = \"ensembles\"\n",
    "\n",
    "def image_path(fig_id):\n",
    "    return os.path.join(PROJECT_ROOT_DIR, \"images\", CHAPTER_ID, fig_id)\n",
    "\n",
    "def save_fig(fig_id, tight_layout=True):\n",
    "    print(\"Saving figure\", fig_id)\n",
    "    if tight_layout:\n",
    "        plt.tight_layout()\n",
    "    plt.savefig(image_path(fig_id) + \".png\", format='png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Voting classifiers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "heads_proba = 0.51\n",
    "coin_tosses = (rnd.rand(10000, 10) < heads_proba).astype(np.int32)\n",
    "cumulative_heads_ratio = np.cumsum(coin_tosses, axis=0) / np.arange(1, 10001).reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure law_of_large_numbers_plot\n"
     ]
    },
    {
     "data": {
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HgnfnPLVrw5P/szq3xWKxWCxnnnPGF9XehnBNnu46Idfo7vda5QkD6jZuTKm5v+fNFGVm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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f35159b4320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,3.5))\n",
    "plt.plot(cumulative_heads_ratio)\n",
    "plt.plot([0, 10000], [0.51, 0.51], \"k--\", linewidth=2, label=\"51%\")\n",
    "plt.plot([0, 10000], [0.5, 0.5], \"k-\", label=\"50%\")\n",
    "plt.xlabel(\"Number of coin tosses\")\n",
    "plt.ylabel(\"Heads ratio\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.axis([0, 10000, 0.42, 0.58])\n",
    "save_fig(\"law_of_large_numbers_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.datasets import make_moons\n",
    "\n",
    "X, y = make_moons(n_samples=500, noise=0.30, random_state=42)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VotingClassifier(estimators=[('lr', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=42, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False)), ('rf', RandomFor...f',\n",
       "  max_iter=-1, probability=False, random_state=42, shrinking=True,\n",
       "  tol=0.001, verbose=False))],\n",
       "         n_jobs=1, voting='hard', weights=None)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import VotingClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "log_clf = LogisticRegression(random_state=42)\n",
    "rnd_clf = RandomForestClassifier(random_state=42)\n",
    "svm_clf = SVC(random_state=42)\n",
    "\n",
    "voting_clf = VotingClassifier(\n",
    "    estimators=[('lr', log_clf), ('rf', rnd_clf), ('svc', svm_clf)],\n",
    "    voting='hard')\n",
    "voting_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LogisticRegression 0.864\n",
      "RandomForestClassifier 0.872\n",
      "SVC 0.888\n",
      "VotingClassifier 0.896\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "for clf in (log_clf, rnd_clf, svm_clf, voting_clf):\n",
    "    clf.fit(X_train, y_train)\n",
    "    y_pred = clf.predict(X_test)\n",
    "    print(clf.__class__.__name__, accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VotingClassifier(estimators=[('lr', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=42, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False)), ('rf', RandomFor...bf',\n",
       "  max_iter=-1, probability=True, random_state=42, shrinking=True,\n",
       "  tol=0.001, verbose=False))],\n",
       "         n_jobs=1, voting='soft', weights=None)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_clf = LogisticRegression(random_state=42)\n",
    "rnd_clf = RandomForestClassifier(random_state=42)\n",
    "svm_clf = SVC(probability=True, random_state=42)\n",
    "\n",
    "voting_clf = VotingClassifier(\n",
    "    estimators=[('lr', log_clf), ('rf', rnd_clf), ('svc', svm_clf)],\n",
    "    voting='soft')\n",
    "voting_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LogisticRegression 0.864\n",
      "RandomForestClassifier 0.872\n",
      "SVC 0.888\n",
      "VotingClassifier 0.912\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "for clf in (log_clf, rnd_clf, svm_clf, voting_clf):\n",
    "    clf.fit(X_train, y_train)\n",
    "    y_pred = clf.predict(X_test)\n",
    "    print(clf.__class__.__name__, accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Bagging ensembles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import BaggingClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "bag_clf = BaggingClassifier(\n",
    "    DecisionTreeClassifier(random_state=42), n_estimators=500,\n",
    "    max_samples=100, bootstrap=True, n_jobs=-1, random_state=42)\n",
    "bag_clf.fit(X_train, y_train)\n",
    "y_pred = bag_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.904\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "print(accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.856\n"
     ]
    }
   ],
   "source": [
    "tree_clf = DecisionTreeClassifier(random_state=42)\n",
    "tree_clf.fit(X_train, y_train)\n",
    "y_pred_tree = tree_clf.predict(X_test)\n",
    "print(accuracy_score(y_test, y_pred_tree))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "def plot_decision_boundary(clf, X, y, axes=[-1.5, 2.5, -1, 1.5], alpha=0.5, contour=True):\n",
    "    x1s = np.linspace(axes[0], axes[1], 100)\n",
    "    x2s = np.linspace(axes[2], axes[3], 100)\n",
    "    x1, x2 = np.meshgrid(x1s, x2s)\n",
    "    X_new = np.c_[x1.ravel(), x2.ravel()]\n",
    "    y_pred = clf.predict(X_new).reshape(x1.shape)\n",
    "    custom_cmap = ListedColormap(['#fafab0','#9898ff','#a0faa0'])\n",
    "    plt.contourf(x1, x2, y_pred, alpha=0.3, cmap=custom_cmap, linewidth=10)\n",
    "    if contour:\n",
    "        custom_cmap2 = ListedColormap(['#7d7d58','#4c4c7f','#507d50'])\n",
    "        plt.contour(x1, x2, y_pred, cmap=custom_cmap2, alpha=0.8)\n",
    "    plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"yo\", alpha=alpha)\n",
    "    plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"bs\", alpha=alpha)\n",
    "    plt.axis(axes)\n",
    "    plt.xlabel(r\"$x_1$\", fontsize=18)\n",
    "    plt.ylabel(r\"$x_2$\", fontsize=18, rotation=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure decision_tree_without_and_with_bagging_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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MInGdyZCo12Yy2tt/FxIIAL1eR0WFgfb236XcVog+r0HGrkokktlEunUBpDZIJNMN2YGQ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4iSG4awWTORveu56c7/uWArzFyYzyZ7hRtSg2WhQADfA/xEyvReD7wmCEKtqqoxUSiCIHwF+Diw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\nhVApcq2Y3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PQALpc/ZXswcDTl89zsHFNXhnF6JwiFrtLS4uLuu381o9Ti4KBmsoIT/eJB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\nIAiCIAiCUDASQAiCIAiCIAiCUDD/P97lnb6k5F3XAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ffa7b1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11,4))\n",
    "plt.subplot(121)\n",
    "plot_decision_boundary(tree_clf, X, y)\n",
    "plt.title(\"Decision Tree\", fontsize=14)\n",
    "plt.subplot(122)\n",
    "plot_decision_boundary(bag_clf, X, y)\n",
    "plt.title(\"Decision Trees with Bagging\", fontsize=14)\n",
    "save_fig(\"decision_tree_without_and_with_bagging_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Random Forests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "bag_clf = BaggingClassifier(\n",
    "    DecisionTreeClassifier(splitter=\"random\", max_leaf_nodes=16, random_state=42),\n",
    "    n_estimators=500, max_samples=1.0, bootstrap=True, n_jobs=-1, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bag_clf.fit(X_train, y_train)\n",
    "y_pred = bag_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rnd_clf = RandomForestClassifier(n_estimators=500, max_leaf_nodes=16, n_jobs=-1, random_state=42)\n",
    "rnd_clf.fit(X_train, y_train)\n",
    "\n",
    "y_pred_rf = rnd_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.97599999999999998"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(y_pred == y_pred_rf) / len(y_pred)  # almost identical predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sepal length (cm) 0.112492250999\n",
      "sepal width (cm) 0.0231192882825\n",
      "petal length (cm) 0.441030464364\n",
      "petal width (cm) 0.423357996355\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "iris = load_iris()\n",
    "rnd_clf = RandomForestClassifier(n_estimators=500, n_jobs=-1, random_state=42)\n",
    "rnd_clf.fit(iris[\"data\"], iris[\"target\"])\n",
    "for name, score in zip(iris[\"feature_names\"], rnd_clf.feature_importances_):\n",
    "    print(name, score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.11249225,  0.02311929,  0.44103046,  0.423358  ])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rnd_clf.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kuRXd2YWx1r0W7t3h4pgLsALb3Jv5nNHxK7pNwqRhMgs0kwRHCk//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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ffafd390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6, 4))\n",
    "\n",
    "for i in range(15):\n",
    "    tree_clf = DecisionTreeClassifier(max_leaf_nodes=16, random_state=42 + i)\n",
    "    indices_with_replacement = rnd.randint(0, len(X_train), len(X_train))\n",
    "    tree_clf.fit(X[indices_with_replacement], y[indices_with_replacement])\n",
    "    plot_decision_boundary(tree_clf, X, y, axes=[-1.5, 2.5, -1, 1.5], alpha=0.02, contour=False)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Out-of-Bag evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.90133333333333332"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bag_clf = BaggingClassifier(\n",
    "    DecisionTreeClassifier(random_state=42), n_estimators=500,\n",
    "    bootstrap=True, n_jobs=-1, oob_score=True, random_state=40)\n",
    "bag_clf.fit(X_train, y_train)\n",
    "bag_clf.oob_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [ 1.        ,  0.        ],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.98989899,  0.01010101],\n",
       "       [ 0.01675978,  0.98324022],\n",
       "       [ 1.        ,  0.        ],\n",
       "       [ 0.13541667,  0.86458333],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.00546448,  0.99453552],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.41836735,  0.58163265],\n",
       "       [ 0.11309524,  0.88690476],\n",
       "       [ 0.22110553,  0.77889447],\n",
       "       [ 1.        ,  0.        ],\n",
       "       [ 0.97647059,  0.02352941],\n",
       "       [ 0.22826087,  0.77173913],\n",
       "       [ 0.98882682,  0.01117318],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 1.        ,  0.        ],\n",
       "       [ 0.96428571,  0.03571429],\n",
       "       [ 0.33507853,  0.66492147],\n",
       "       [ 0.98235294,  0.01764706],\n",
       "       [ 1.        ,  0.        ],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.99465241,  0.00534759],\n",
       "       [ 0.        ,  1.        ],\n",
       "       [ 0.06043956,  0.93956044],\n",
       "       [ 0.97619048,  0.02380952],\n",
       "       [ 1.        ,  0.        ],\n",
       "       [ 0.03108808,  0.96891192],\n",
       "       [ 0.57291667,  0.42708333]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bag_clf.oob_decision_function_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.91200000000000003"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "y_pred = bag_clf.predict(X_test)\n",
    "accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Feature importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from sklearn.datasets import fetch_mldata\n",
    "mnist = fetch_mldata('MNIST original')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
       "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "            n_estimators=10, n_jobs=1, oob_score=False, random_state=42,\n",
       "            verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rnd_clf = RandomForestClassifier(random_state=42)\n",
    "rnd_clf.fit(mnist[\"data\"], mnist[\"target\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def plot_digit(data):\n",
    "    image = data.reshape(28, 28)\n",
    "    plt.imshow(image, cmap = matplotlib.cm.hot,\n",
    "               interpolation=\"nearest\")\n",
    "    plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure mnist_feature_importance_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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0CBEA9bCclR4hAqAeZiLpESIA6iFE0iNEANTDclZ6hAiAapiI5DeQmw2nBmpKe6Be0o+B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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ff9e3978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_digit(rnd_clf.feature_importances_)\n",
    "\n",
    "cbar = plt.colorbar(ticks=[rnd_clf.feature_importances_.min(), rnd_clf.feature_importances_.max()])\n",
    "cbar.ax.set_yticklabels(['Not important', 'Very important'])\n",
    "\n",
    "save_fig(\"mnist_feature_importance_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# AdaBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AdaBoostClassifier(algorithm='SAMME.R',\n",
       "          base_estimator=DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=1,\n",
       "            max_features=None, max_leaf_nodes=None,\n",
       "            min_impurity_split=1e-07, min_samples_leaf=1,\n",
       "            min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "            presort=False, random_state=None, splitter='best'),\n",
       "          learning_rate=0.5, n_estimators=200, random_state=42)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "\n",
    "ada_clf = AdaBoostClassifier(\n",
    "    DecisionTreeClassifier(max_depth=1), n_estimators=200,\n",
    "    algorithm=\"SAMME.R\", learning_rate=0.5, random_state=42)\n",
    "ada_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SDJx0dY2Sm+tMuI+pCK50WAJLtdZjOWf8yY7pxVa4q8XyWE5UpRJCps2CAqQ6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\nTEOUiiAIgmAa/x8j8I7eW0iKsgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ff9e3eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_decision_boundary(ada_clf, X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure boosting_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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7CLoIG2HxZq6/feVYdC2gqAHEVYo/Rn4wQzheMaUj8SKN1qD7EplAeOsU40Nb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QR8aJGtzC21YDBIaFo3F6u3EiAy6NjsPDd1tc8hyQZkQ4gUVx7IMvkTXI1RNQ1ZNmOyGcjJTx4x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\nzjSAEBERERGRnP0/v4YhwwUxK/QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ff9bba58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = len(X_train)\n",
    "\n",
    "plt.figure(figsize=(11, 4))\n",
    "for subplot, learning_rate in ((121, 1), (122, 0.5)):\n",
    "    sample_weights = np.ones(m)\n",
    "    for i in range(5):\n",
    "        plt.subplot(subplot)\n",
    "        svm_clf = SVC(kernel=\"rbf\", C=0.05)\n",
    "        svm_clf.fit(X_train, y_train, sample_weight=sample_weights)\n",
    "        y_pred = svm_clf.predict(X_train)\n",
    "        sample_weights[y_pred != y_train] *= (1 + learning_rate)\n",
    "        plot_decision_boundary(svm_clf, X, y, alpha=0.2)\n",
    "        plt.title(\"learning_rate = {}\".format(learning_rate - 1), fontsize=16)\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.text(-0.7, -0.65, \"1\", fontsize=14)\n",
    "plt.text(-0.6, -0.10, \"2\", fontsize=14)\n",
    "plt.text(-0.5,  0.10, \"3\", fontsize=14)\n",
    "plt.text(-0.4,  0.55, \"4\", fontsize=14)\n",
    "plt.text(-0.3,  0.90, \"5\", fontsize=14)\n",
    "save_fig(\"boosting_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['base_estimator_',\n",
       " 'classes_',\n",
       " 'estimator_errors_',\n",
       " 'estimator_weights_',\n",
       " 'estimators_',\n",
       " 'feature_importances_',\n",
       " 'n_classes_']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(m for m in dir(ada_clf) if not m.startswith(\"_\") and m.endswith(\"_\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Gradient Boosting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rnd.seed(42)\n",
    "X = rnd.rand(100, 1) - 0.5\n",
    "y = 3*X[:, 0]**2 + 0.05 * rnd.randn(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
       "           max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "           min_samples_leaf=1, min_samples_split=2,\n",
       "           min_weight_fraction_leaf=0.0, presort=False, random_state=42,\n",
       "           splitter='best')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "\n",
    "tree_reg1 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
    "tree_reg1.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
       "           max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "           min_samples_leaf=1, min_samples_split=2,\n",
       "           min_weight_fraction_leaf=0.0, presort=False, random_state=42,\n",
       "           splitter='best')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y2 = y - tree_reg1.predict(X)\n",
    "tree_reg2 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
    "tree_reg2.fit(X, y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
       "           max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "           min_samples_leaf=1, min_samples_split=2,\n",
       "           min_weight_fraction_leaf=0.0, presort=False, random_state=42,\n",
       "           splitter='best')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y3 = y2 - tree_reg2.predict(X)\n",
    "tree_reg3 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
    "tree_reg3.fit(X, y3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_new = np.array([[0.8]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_pred = sum(tree.predict(X_new) for tree in (tree_reg1, tree_reg2, tree_reg3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.75026781])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure gradient_boosting_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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6lU996lOcdtppnHfeebzxxhtMnTqVoUOH0tCQvdfjCSecwEc+8hHGjh3LwIED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\nLCAkSZIklWYBIUmSJKk0CwhJkiRJpf0fVyUygK9EZNAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f351cf33a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_predictions(regressors, X, y, axes, label=None, style=\"r-\", data_style=\"b.\", data_label=None):\n",
    "    x1 = np.linspace(axes[0], axes[1], 500)\n",
    "    y_pred = sum(regressor.predict(x1.reshape(-1, 1)) for regressor in regressors)\n",
    "    plt.plot(X[:, 0], y, data_style, label=data_label)\n",
    "    plt.plot(x1, y_pred, style, linewidth=2, label=label)\n",
    "    if label or data_label:\n",
    "        plt.legend(loc=\"upper center\", fontsize=16)\n",
    "    plt.axis(axes)\n",
    "\n",
    "plt.figure(figsize=(11,11))\n",
    "\n",
    "plt.subplot(321)\n",
    "plot_predictions([tree_reg1], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h_1(x_1)$\", style=\"g-\", data_label=\"Training set\")\n",
    "plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
    "plt.title(\"Residuals and tree predictions\", fontsize=16)\n",
    "\n",
    "plt.subplot(322)\n",
    "plot_predictions([tree_reg1], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1)$\", data_label=\"Training set\")\n",
    "plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
    "plt.title(\"Ensemble predictions\", fontsize=16)\n",
    "\n",
    "plt.subplot(323)\n",
    "plot_predictions([tree_reg2], X, y2, axes=[-0.5, 0.5, -0.5, 0.5], label=\"$h_2(x_1)$\", style=\"g-\", data_style=\"k+\", data_label=\"Residuals\")\n",
    "plt.ylabel(\"$y - h_1(x_1)$\", fontsize=16)\n",
    "\n",
    "plt.subplot(324)\n",
    "plot_predictions([tree_reg1, tree_reg2], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1) + h_2(x_1)$\")\n",
    "plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
    "\n",
    "plt.subplot(325)\n",
    "plot_predictions([tree_reg3], X, y3, axes=[-0.5, 0.5, -0.5, 0.5], label=\"$h_3(x_1)$\", style=\"g-\", data_style=\"k+\")\n",
    "plt.ylabel(\"$y - h_1(x_1) - h_2(x_1)$\", fontsize=16)\n",
    "plt.xlabel(\"$x_1$\", fontsize=16)\n",
    "\n",
    "plt.subplot(326)\n",
    "plot_predictions([tree_reg1, tree_reg2, tree_reg3], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1) + h_2(x_1) + h_3(x_1)$\")\n",
    "plt.xlabel(\"$x_1$\", fontsize=16)\n",
    "plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
    "\n",
    "save_fig(\"gradient_boosting_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
       "             learning_rate=1.0, loss='ls', max_depth=2, max_features=None,\n",
       "             max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "             min_samples_leaf=1, min_samples_split=2,\n",
       "             min_weight_fraction_leaf=0.0, n_estimators=3, presort='auto',\n",
       "             random_state=42, subsample=1.0, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "\n",
    "gbrt = GradientBoostingRegressor(max_depth=2, n_estimators=3, learning_rate=1.0, random_state=42)\n",
    "gbrt.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
       "             learning_rate=0.1, loss='ls', max_depth=2, max_features=None,\n",
       "             max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "             min_samples_leaf=1, min_samples_split=2,\n",
       "             min_weight_fraction_leaf=0.0, n_estimators=200,\n",
       "             presort='auto', random_state=42, subsample=1.0, verbose=0,\n",
       "             warm_start=False)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gbrt_slow = GradientBoostingRegressor(max_depth=2, n_estimators=200, learning_rate=0.1, random_state=42)\n",
    "gbrt_slow.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure gbrt_learning_rate_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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ZDBs2jCFDhtCvXz+MMTz66KNcdtll5OfnM2DAgJCLC957770MGzaMM844g2uv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\nEkFjQ4IlIjbUfhc/dQaXagKhEm3LFnjqKdjpDGz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7IIrcSE6xoUSpxO3gxCk0Aq0vPwvX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\nhIiIiIiI+Pb/vmUQQVZ+/zAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ffa69780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11,4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plot_predictions([gbrt], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"Ensemble predictions\")\n",
    "plt.title(\"learning_rate={}, n_estimators={}\".format(gbrt.learning_rate, gbrt.n_estimators), fontsize=14)\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_predictions([gbrt_slow], X, y, axes=[-0.5, 0.5, -0.1, 0.8])\n",
    "plt.title(\"learning_rate={}, n_estimators={}\".format(gbrt_slow.learning_rate, gbrt_slow.n_estimators), fontsize=14)\n",
    "\n",
    "save_fig(\"gbrt_learning_rate_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Gradient Boosting with Early stopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
       "             learning_rate=0.1, loss='ls', max_depth=2, max_features=None,\n",
       "             max_leaf_nodes=None, min_impurity_split=1e-07,\n",
       "             min_samples_leaf=1, min_samples_split=2,\n",
       "             min_weight_fraction_leaf=0.0, n_estimators=55, presort='auto',\n",
       "             random_state=42, subsample=1.0, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "X_train, X_val, y_train, y_val = train_test_split(X, y, random_state=49)\n",
    "\n",
    "gbrt = GradientBoostingRegressor(max_depth=2, n_estimators=120, random_state=42)\n",
    "gbrt.fit(X_train, y_train)\n",
    "\n",
    "errors = [mean_squared_error(y_val, y_pred)\n",
    "          for y_pred in gbrt.staged_predict(X_val)]\n",
    "bst_n_estimators = np.argmin(errors)\n",
    "\n",
    "gbrt_best = GradientBoostingRegressor(max_depth=2,n_estimators=bst_n_estimators, random_state=42)\n",
    "gbrt_best.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "min_error = np.min(errors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving figure early_stopping_gbrt_plot\n"
     ]
    },
    {
     "data": {
      "image/png": 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mNtDMBgI/IKR0A8DMis2sG2FoUhcz6xqbFPQn4DQzGx3Ne/h/8efmw8iR8N57+ayBiEhh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\nPn5389rBoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34ffa0d518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11, 4))\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.plot(errors, \"b.-\")\n",
    "plt.plot([bst_n_estimators, bst_n_estimators], [0, min_error], \"k--\")\n",
    "plt.plot([0, 120], [min_error, min_error], \"k--\")\n",
    "plt.plot(bst_n_estimators, min_error, \"ko\")\n",
    "plt.text(bst_n_estimators, min_error*1.2, \"Minimum\", ha=\"center\", fontsize=14)\n",
    "plt.axis([0, 120, 0, 0.01])\n",
    "plt.xlabel(\"Number of trees\")\n",
    "plt.title(\"Validation error\", fontsize=14)\n",
    "\n",
    "plt.subplot(122)\n",
    "plot_predictions([gbrt_best], X, y, axes=[-0.5, 0.5, -0.1, 0.8])\n",
    "plt.title(\"Best model (%d trees)\" % bst_n_estimators, fontsize=14)\n",
    "\n",
    "save_fig(\"early_stopping_gbrt_plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "gbrt = GradientBoostingRegressor(max_depth=2, warm_start=True, random_state=42)\n",
    "\n",
    "min_val_error = float(\"inf\")\n",
    "error_going_up = 0\n",
    "for n_estimators in range(1, 120):\n",
    "    gbrt.n_estimators = n_estimators\n",
    "    gbrt.fit(X_train, y_train)\n",
    "    y_pred = gbrt.predict(X_val)\n",
    "    val_error = mean_squared_error(y_val, y_pred)\n",
    "    if val_error < min_val_error:\n",
    "        min_val_error = val_error\n",
    "        error_going_up = 0\n",
    "    else:\n",
    "        error_going_up += 1\n",
    "        if error_going_up == 5:\n",
    "            break  # early stopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "61\n"
     ]
    }
   ],
   "source": [
    "print(gbrt.n_estimators)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Exercise solutions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Coming soon**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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